ARTE Y PODER

El presente trabajo no tiene por objetivo ni definir el arte, ni hacer una crítica sobre los procesos llevados a cabo en el medio artístico; sin embargo, busca poner en el tapete la discusión sobre la efectividad simbólica del arte; cómo su carácter comunicacional puede ser utilizado por el poder y cómo, a través de la historia, el arte ha colaborado con procesos de dominación. En el texto no se intenta definir el arte, por el contrario, se menciona el pensamiento de Croce sobre lo que no debería ser, con el fin de establecer la razón por la que ciertas concepciones han utilizado el arte como medio de propaganda política. Posteriormente, se vincula al arte como símbolo, identificándolo como una construcción cargada de significados, inherentes a su época pero con vigencia en los imaginarios; al estar cargado de significados considero que el arte trata de hacer una revisión somera sobre sí mismo, con algunos hitos relevantes, con la aclaración que está sujeto a una historia del arte occidental

HTself2: Combining p-values to Improve Classification of Differential Gene Expression in HTself

HTself is a web-based bioinformatics tool designed to deal with the classification of differential gene expression for low replication microarray studies. It is based on a statistical test that uses self-self experiments to derive intensity-dependent cutoffs. The method was previously described in Vêncio et al, (DNA Res. 12: 211- e 214, 2005). In this work we consider an extension of HTself by calculating p-values instead of using a fixed credibility level α. As before, the statistic used to compute single spots p-values is obtained from the gaussian Kernel Density Estimator method applied to self-self data. Different spots corresponding to the same biological gene (replicas) give rise to a set of independent p-values which can be combined by well known statistical methods. The combined p-value can be used to decide whether a gene can be considered differentially expressed or not. HTself2 is a new version of HTself that uses the idea of p-values combination. It was implemented as a user-friendly desktop application to help laboratories without a bioinformatics infrastructure

Microswitches with Sputtered Au, AuPd,Au-on-AuPt, and AuPtCu Alloy Electric Contacts

This paper is the first to report on a new analytic model for predicting microcontact resistance and the design, fabrication, and testing of microelectromechanical systems (MEMS) metal contact switches with sputtered bimetallic (i.e., gold (Au)-on-Au-platinum (Pt), (Au-on-Au-(6.3at%)Pt)), binary alloy (i.e., Au-palladium (Pd), (Au-(3.7at%)Pd)), and ternary alloy (i.e., Au-Pt-copper (Cu), (Au-(5.0at%)Pt-(0.5at%)Cu)) electric contacts. The microswitches with bimetallic and binary alloy contacts resulted in contact resistance values between 1-2Omega. Preliminary reliability testing indicates a 3times increase in switching lifetime when compared to microswitches with sputtered Au electric contacts. The ternary alloy exhibited approximately a 6times increase in switch lifetime with contact resistance values ranging from approximately 0.2-1.8Omeg

Micro-Switches with Sputtered Au, AuPd, Au-on-AuPt, and AuPtCu Alloy Electric Contacts

This work is the first to report on a new analytic model for predicting micro-contact resistance and the design, fabrication, and testing of microelectromechanical systems (MEMS) metal contact switches with sputtered bi-metallic (i.e. gold (Au)-on-Au-platinum (Pt), (Au-on-Au-(6%)Pt)), binary alloy (i.e. Au-palladium (Pd), (Au-(2%)Pd)), and tertiary alloy (i.e. Au-Pt-copper (Cu), (Au-(5%)Pt-(0.5%)Cu)) electric contacts. The micro-switches with bi-metallic and binary alloy contacts resulted in contact resistance between 1-2 /spl Omega/ and, when compared to micro-switches with sputtered Au electric contacts, exhibited a 3.3 and 2.6 times increase in switching lifetime, respectively. The tertiary alloy exhibited a 6.5 times increase in switch lifetime with contact resistance ranging from 0.2-1.8 /spl Omega/

Data mining with neural networks and support vector machines using the R/rminer tool

We present rminer, our open source library for the R tool that facilitates the use of data mining (DM) algorithms, such as neural Networks (NNs) and support vector machines (SVMs), in classification and regression tasks. Tutorial examples with real-world problems (i.e. satellite image analysis and prediction of car prices) were used to demonstrate the rminer capabilities and NN/SVM advantages. Additional experiments were also held to test the rminer predictive capabilities, revealing competitive performances.Fundação para a Ciência e a Tecnologia (FCT) - PTDC/EIA/64541/200

Using customer lifetime value and neural networks to improve the prediction of bank deposit subscription in telemarketing campaigns

Customer lifetime value (LTV) enables using client characteristics, such as recency, frequency and monetary value, to describe the value of a client through time in terms of profitability. We present the concept of LTV applied to telemarketing for improving the return-on-investment, using a recent (from 2008 to 2013) and real case study of bank campaigns to sell long-term deposits. The goal was to benefit from past contacts history to extract additional knowledge. A total of twelve LTV input variables were tested, under a forward selection method and using a realistic rolling windows scheme, highlighting the validity of five new LTV features. The results achieved by our LTV data-driven approach using neural networks allowed an improvement up to 4 pp in the Lift cumulative curve for targeting the deposit subscribers when compared with a baseline model (with no history data). Explanatory knowledge was also extracted from the proposed model, revealing two highly relevant LTV features, the last result of the previous campaign to sell the same product and the frequency of past client successes. The obtained results are particularly valuable for contact center companies, which can improve predictive performance without even having to ask for more information to the companies they serve.info:eu-repo/semantics/acceptedVersio

Denitrification of a landfill leachate with high nitrate concentration in an anoxic rotating biological contactor

The denitrification performance of a lab-scale anoxic rotating biological contactor (RBC) using landfill leachate with high nitrate concentration was evaluated. Under a carbon to nitrogen ratio (C/N) of 2, the reactor achieved N-NO3 − removal efficiencies above 95% for concentrations up to 100 mg N-NO3 − l−1. The highest observed denitrification rate was 55 mg N-NO3 − l−1 h−1 (15 g N-NO3 − m−2 d−1) at a nitrate concentration of 560 mg N-NO3 − l−1. Although the reactor has revealed a very good performance in terms of denitrification, effluent chemical oxygen demand (COD) concentrations were still high for direct discharge. The results obtained in a subsequent experiment at constant nitrate concentration (220 mg N-NO3 − l−1) and lower C/N ratios (1.2 and 1.5) evidenced that the organic matter present in the leachate was non-biodegradable. A phosphorus concentration of 10 mg P-PO4 3− l−1 promoted autotrophic denitrification, revealing the importance of phosphorus concentration on biological denitrification processes.Susana Cortez and Pilar Teixeira are grateful to Fundacao para a Ciencia e Tecnologia (FCT) for financial support through the grants SFRH/BD/24715/2005 and SFRH/BPD/26803/2006, respectively

Applying knowledge management strategies to economic development in sub-Saharan Africa

Sustainability looks to achieve best outcomes for human and natural environments both now and in the indefinite future. It relates to the continuity of economic, social, institutional and environmental aspects of human society, as well as the non-human environment. This paper examines economic development as one aspect of sustainability, with a focus on knowledge management as an economic development strategy. Using Grey’s categories of knowledge management, the authors address sustainable economic development in the context of sub-Saharan Africa. Production capability is no longer completely dependent on capital and equipment; information and knowledge assets are increasingly important. In this information economy, success comes from harnessing the information and knowledge of a community. Such “indigenous knowledge,” local and often tacit, exists in every community, every region and every country. This knowledge is useful in identifying new entrepreneurial opportunities, as well as for sustaining and advancing local businesses. Sub-Saharan Africa provides an excellent case study. No other region of the world is in more dire need of development. The 700 million people in this area face tremendous challenges, including the world’s highest incidence of HIV/AIDS, deep poverty, unemployment, political instability, and a host of related problems. Key factors for using knowledge management as an economic development strategy in the region will include ICT (Information and Communication Technologies) literacy; uncovering and developing local intellectual assets; capturing tacit knowledge; internal and external knowledge sharing; and managing political, social and technological barriers. Other specific recommendations include promoting ICT literacy through training programs; leveraging internet and email technologies for community building; investing financial resources in R & D; and developing metrics for outcome assessment.Keywords: Knowledge management, economic development, sub-Saharan Africa